The Latest Metabolic Syndrome Research and News

Month: August 2014

http://ift.tt/1pZkwir A new study finds the five highest comorbidities of sudden unexpected death in North Carolina are hypertension, diabetes mellitus, dyslipidemia, coronary heart disease, and cardiomyopathy.

http://ift.tt/1u368Wu To the careful observer, a person’s face has long provided insight into what is going on beneath the surface. Now, with the assistance of a web camera and software algorithms, the face can also reveal whether or not an individual is experiencing atrial fibrillation, a treatable but potentially dangerous heart condition.

http://ift.tt/1wX2bHH A new study finds the five highest comorbidities of sudden unexpected death in North Carolina are hypertension, diabetes mellitus, dyslipidemia, coronary heart disease, and cardiomyopathy.

http://ift.tt/1wX2baz For better heart health, rich countries should continue to deliver high quality health care while trying to reduce risk factors, while poor countries need to avoid the rise of risk factors but also substantially improve their health care.

http://ift.tt/1qXHKp7 Oxidized lipids are known to play a key role in inflaming blood vessels and hardening arteries, which causes diseases like atherosclerosis. A new study demonstrates that they may also contribute to pulmonary hypertension, a serious lung disease that narrows the small blood vessels in the lungs. Using a rodent model, the researchers showed that a peptide mimicking part of the main protein in HDL, the so-called “good” cholesterol, may help reduce the production of oxidized lipids in pulmonary hypertension.

http://ift.tt/1zYGa7i A new model has been developed for predicting which patients with type 1 diabetes will go on to develop major complications, through easily and routinely measured risk factors. “The risk estimates can guide surveillance recommendations, inform patients and allow efficient design and analysis of clinical trials,” the author say.

http://ift.tt/1pffSaJ A new model has been developed for predicting which patients with type 1 diabetes will go on to develop major complications, through easily and routinely measured risk factors. “The risk estimates can guide surveillance recommendations, inform patients and allow efficient design and analysis of clinical trials,” the author say.